Open Access Highly Accessed Open Badges Methodology article

Combining next-generation pyrosequencing with microarray for large scale expression analysis in non-model species

Diana Bellin1, Alberto Ferrarini1, Antonio Chimento1, Olaf Kaiser2, Natasha Levenkova3, Pascal Bouffard3 and Massimo Delledonne1*

Author Affiliations

1 Department of Biotechnology, University of Verona, Strada le Grazie 15, 37134 Verona, Italy

2 Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany

3 454 Life Sciences, 1 Commercial Street, Branford, CT 06405, USA

For all author emails, please log on.

BMC Genomics 2009, 10:555  doi:10.1186/1471-2164-10-555

Published: 24 November 2009



The next generation sequencing technologies provide new options to characterize the transcriptome and to develop affordable tools for functional genomics. We describe here an innovative approach for this purpose and demonstrate its potential also for non-model species.


The method we developed is based on 454 sequencing of 3' cDNA fragments from a normalized library constructed from pooled RNAs to generate, through de novo reads assembly, a large catalog of unique transcripts in organisms for which a comprehensive collection of transcripts or the complete genome sequence, is not available. This "virtual transcriptome" provides extensive coverage depth, and can be used for the setting up of a comprehensive microarray based expression analysis. We evaluated the potential of this approach by monitoring gene expression during berry maturation in Vitis vinifera as if no other sequence information was available for this species. The microarray designed on the berries' transcriptome derived from half of a 454 run detected the expression of 19,609 genes, and proved to be more informative than one of the most comprehensive grape microarrays available to date, the GrapeArray 1.2 developed by the Italian-French Public Consortium for Grapevine Genome Characterization, which could detect the expression of 15,556 genes in the same samples.


This approach provides a powerful method to rapidly build up an extensive catalog of unique transcripts that can be successfully used to develop a microarray for large scale analysis of gene expression in any species, without the need for prior sequence knowledge.